AI Medical Compendium Journal:
Acta ophthalmologica

Showing 11 to 20 of 27 articles

Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning.

Acta ophthalmologica
PURPOSE: To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomography (AS-OCT): The intraocular lens (IOL), the retrolental space (IOL to the posterior lens capsule) an...

Prediction of the axial lens position after cataract surgery using deep learning algorithms and multilinear regression.

Acta ophthalmologica
BACKGROUND: The prediction of anatomical axial intraocular lens position (ALP) is one of the major challenges in cataract surgery. The purpose of this study was to develop and test prediction algorithms for ALP based on deep learning strategies.

Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.

Acta ophthalmologica
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...

Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data.

Acta ophthalmologica
PURPOSE: To meet the demands imposed by the continuing growth of the Age-related macular degeneration (AMD) patient population, automation of follow-ups by detecting retinal oedema using deep learning might be a viable approach. However, preparing an...

Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...

Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.

Acta ophthalmologica
PURPOSE: To validate the performance of a commercially available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Netherlands), for the joint automatic detection of diabetic retinopathy (DR) and age-related macular dege...

Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.

Acta ophthalmologica
BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a diagnostic decision but also performs quantitative analysis of the typical pathological features of t...